epoch 0: {'accuracy': 0.4729241877256318} , current_best_acc: 0.4729241877256318 train_loss: 0.7035874724388123
epoch 1: {'accuracy': 0.5270758122743683} , current_best_acc: 0.5270758122743683 train_loss: 0.7094193696975708
epoch 2: {'accuracy': 0.5956678700361011} , current_best_acc: 0.5956678700361011 train_loss: 0.7267389297485352
epoch 3: {'accuracy': 0.631768953068592} , current_best_acc: 0.631768953068592 train_loss: 0.6787453293800354
epoch 4: {'accuracy': 0.4729241877256318} , current_best_acc: 0.631768953068592 train_loss: 0.8288853764533997
epoch 5: {'accuracy': 0.6173285198555957} , current_best_acc: 0.631768953068592 train_loss: 0.6277210712432861
epoch 6: {'accuracy': 0.5415162454873647} , current_best_acc: 0.631768953068592 train_loss: 0.7471601963043213
epoch 7: {'accuracy': 0.5595667870036101} , current_best_acc: 0.631768953068592 train_loss: 0.651648759841919
epoch 8: {'accuracy': 0.6534296028880866} , current_best_acc: 0.6534296028880866 train_loss: 0.5243284702301025
epoch 9: {'accuracy': 0.7111913357400722} , current_best_acc: 0.7111913357400722 train_loss: 0.7257586717605591
epoch 10: {'accuracy': 0.7111913357400722} , current_best_acc: 0.7111913357400722 train_loss: 0.5404270887374878
epoch 11: {'accuracy': 0.7111913357400722} , current_best_acc: 0.7111913357400722 train_loss: 0.6011591553688049
epoch 12: {'accuracy': 0.628158844765343} , current_best_acc: 0.7111913357400722 train_loss: 0.8276504874229431
epoch 13: {'accuracy': 0.7472924187725631} , current_best_acc: 0.7472924187725631 train_loss: 0.3643234670162201
epoch 14: {'accuracy': 0.7075812274368231} , current_best_acc: 0.7472924187725631 train_loss: 0.5689178705215454
epoch 15: {'accuracy': 0.7978339350180506} , current_best_acc: 0.7978339350180506 train_loss: 0.8334299325942993
epoch 16: {'accuracy': 0.7472924187725631} , current_best_acc: 0.7978339350180506 train_loss: 0.3917105793952942
epoch 17: {'accuracy': 0.7978339350180506} , current_best_acc: 0.7978339350180506 train_loss: 0.30931371450424194
epoch 18: {'accuracy': 0.7472924187725631} , current_best_acc: 0.7978339350180506 train_loss: 0.23067568242549896
epoch 19: {'accuracy': 0.776173285198556} , current_best_acc: 0.7978339350180506 train_loss: 0.36001908779144287
epoch 20: {'accuracy': 0.7184115523465704} , current_best_acc: 0.7978339350180506 train_loss: 0.5046104192733765
epoch 21: {'accuracy': 0.779783393501805} , current_best_acc: 0.7978339350180506 train_loss: 0.5431627035140991
epoch 22: {'accuracy': 0.740072202166065} , current_best_acc: 0.7978339350180506 train_loss: 0.32459309697151184
epoch 23: {'accuracy': 0.7472924187725631} , current_best_acc: 0.7978339350180506 train_loss: 0.570236086845398
epoch 24: {'accuracy': 0.7292418772563177} , current_best_acc: 0.7978339350180506 train_loss: 0.278042733669281
epoch 25: {'accuracy': 0.7942238267148014} , current_best_acc: 0.7978339350180506 train_loss: 0.4669194221496582
epoch 26: {'accuracy': 0.7725631768953068} , current_best_acc: 0.7978339350180506 train_loss: 0.5375593900680542
epoch 27: {'accuracy': 0.7581227436823105} , current_best_acc: 0.7978339350180506 train_loss: 0.33120983839035034
epoch 28: {'accuracy': 0.7689530685920578} , current_best_acc: 0.7978339350180506 train_loss: 0.20130151510238647
epoch 29: {'accuracy': 0.7581227436823105} , current_best_acc: 0.7978339350180506 train_loss: 0.2608753442764282
epoch 30: {'accuracy': 0.7906137184115524} , current_best_acc: 0.7978339350180506 train_loss: 0.11878138035535812
epoch 31: {'accuracy': 0.7870036101083032} , current_best_acc: 0.7978339350180506 train_loss: 0.36379387974739075
epoch 32: {'accuracy': 0.8086642599277978} , current_best_acc: 0.8086642599277978 train_loss: 0.3868759572505951
epoch 33: {'accuracy': 0.8050541516245487} , current_best_acc: 0.8086642599277978 train_loss: 0.15403181314468384
epoch 34: {'accuracy': 0.7725631768953068} , current_best_acc: 0.8086642599277978 train_loss: 0.12917959690093994
epoch 35: {'accuracy': 0.8303249097472925} , current_best_acc: 0.8303249097472925 train_loss: 0.28165748715400696
epoch 36: {'accuracy': 0.7833935018050542} , current_best_acc: 0.8303249097472925 train_loss: 0.3544107675552368
epoch 37: {'accuracy': 0.7725631768953068} , current_best_acc: 0.8303249097472925 train_loss: 0.40713581442832947
epoch 38: {'accuracy': 0.740072202166065} , current_best_acc: 0.8303249097472925 train_loss: 0.28231966495513916
epoch 39: {'accuracy': 0.776173285198556} , current_best_acc: 0.8303249097472925 train_loss: 0.1448782980442047
epoch 40: {'accuracy': 0.7870036101083032} , current_best_acc: 0.8303249097472925 train_loss: 0.3418356776237488
epoch 41: {'accuracy': 0.7689530685920578} , current_best_acc: 0.8303249097472925 train_loss: 0.33313459157943726
epoch 42: {'accuracy': 0.8375451263537906} , current_best_acc: 0.8375451263537906 train_loss: 0.2302306741476059
epoch 43: {'accuracy': 0.779783393501805} , current_best_acc: 0.8375451263537906 train_loss: 0.20717523992061615
epoch 44: {'accuracy': 0.7581227436823105} , current_best_acc: 0.8375451263537906 train_loss: 0.07359416782855988
epoch 45: {'accuracy': 0.7436823104693141} , current_best_acc: 0.8375451263537906 train_loss: 0.3839282691478729
epoch 46: {'accuracy': 0.8158844765342961} , current_best_acc: 0.8375451263537906 train_loss: 0.228291854262352
epoch 47: {'accuracy': 0.740072202166065} , current_best_acc: 0.8375451263537906 train_loss: 0.17193038761615753
epoch 48: {'accuracy': 0.8158844765342961} , current_best_acc: 0.8375451263537906 train_loss: 0.1687297523021698
epoch 49: {'accuracy': 0.7906137184115524} , current_best_acc: 0.8375451263537906 train_loss: 0.23515485227108002
epoch 50: {'accuracy': 0.7942238267148014} , current_best_acc: 0.8375451263537906 train_loss: 0.2462538182735443
epoch 51: {'accuracy': 0.7581227436823105} , current_best_acc: 0.8375451263537906 train_loss: 0.08791395276784897
epoch 52: {'accuracy': 0.8339350180505415} , current_best_acc: 0.8375451263537906 train_loss: 0.1213991567492485
epoch 53: {'accuracy': 0.7509025270758123} , current_best_acc: 0.8375451263537906 train_loss: 0.12228670716285706
epoch 54: {'accuracy': 0.7472924187725631} , current_best_acc: 0.8375451263537906 train_loss: 0.1923813819885254
epoch 55: {'accuracy': 0.7617328519855595} , current_best_acc: 0.8375451263537906 train_loss: 0.2539116442203522
epoch 56: {'accuracy': 0.8050541516245487} , current_best_acc: 0.8375451263537906 train_loss: 0.06396815180778503
epoch 57: {'accuracy': 0.8086642599277978} , current_best_acc: 0.8375451263537906 train_loss: 0.05286787077784538
epoch 58: {'accuracy': 0.7978339350180506} , current_best_acc: 0.8375451263537906 train_loss: 0.0814051628112793
epoch 59: {'accuracy': 0.8014440433212996} , current_best_acc: 0.8375451263537906 train_loss: 0.14419835805892944
epoch 60: {'accuracy': 0.7472924187725631} , current_best_acc: 0.8375451263537906 train_loss: 0.2625126242637634
epoch 61: {'accuracy': 0.7617328519855595} , current_best_acc: 0.8375451263537906 train_loss: 0.030704818665981293
epoch 62: {'accuracy': 0.8267148014440433} , current_best_acc: 0.8375451263537906 train_loss: 0.12273840606212616
epoch 63: {'accuracy': 0.7689530685920578} , current_best_acc: 0.8375451263537906 train_loss: 0.07056932896375656
epoch 64: {'accuracy': 0.8050541516245487} , current_best_acc: 0.8375451263537906 train_loss: 0.011763762682676315
epoch 65: {'accuracy': 0.7870036101083032} , current_best_acc: 0.8375451263537906 train_loss: 0.25790056586265564
epoch 66: {'accuracy': 0.8014440433212996} , current_best_acc: 0.8375451263537906 train_loss: 0.011716245673596859
epoch 67: {'accuracy': 0.7978339350180506} , current_best_acc: 0.8375451263537906 train_loss: 0.026239756494760513
epoch 68: {'accuracy': 0.7942238267148014} , current_best_acc: 0.8375451263537906 train_loss: 0.13102459907531738
epoch 69: {'accuracy': 0.7833935018050542} , current_best_acc: 0.8375451263537906 train_loss: 0.18594612181186676
epoch 70: {'accuracy': 0.7653429602888087} , current_best_acc: 0.8375451263537906 train_loss: 0.04949904978275299
epoch 71: {'accuracy': 0.7509025270758123} , current_best_acc: 0.8375451263537906 train_loss: 0.1647719442844391
epoch 72: {'accuracy': 0.7689530685920578} , current_best_acc: 0.8375451263537906 train_loss: 0.3861355781555176
epoch 73: {'accuracy': 0.7906137184115524} , current_best_acc: 0.8375451263537906 train_loss: 0.06721001863479614
epoch 74: {'accuracy': 0.7906137184115524} , current_best_acc: 0.8375451263537906 train_loss: 0.0757998675107956
epoch 75: {'accuracy': 0.7906137184115524} , current_best_acc: 0.8375451263537906 train_loss: 0.018379556015133858
epoch 76: {'accuracy': 0.8050541516245487} , current_best_acc: 0.8375451263537906 train_loss: 0.0032764540519565344
epoch 77: {'accuracy': 0.7906137184115524} , current_best_acc: 0.8375451263537906 train_loss: 0.020852021872997284
epoch 78: {'accuracy': 0.7870036101083032} , current_best_acc: 0.8375451263537906 train_loss: 0.05743001028895378
epoch 79: {'accuracy': 0.7906137184115524} , current_best_acc: 0.8375451263537906 train_loss: 0.01059098169207573
